{
 "cells": [
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# # 3、手动设置搜索参数，编写for循环实现网格搜索",
   "id": "650020929f2bad3c"
  },
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2025-03-07T12:23:17.365288Z",
     "start_time": "2025-03-07T12:23:17.362449Z"
    }
   },
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import sklearn\n",
    "from tqdm.auto import tqdm\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import os\n",
    "import sys\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "from torchvision import datasets\n",
    "from torchvision import transforms  # 将图片转换为tensor"
   ],
   "outputs": [],
   "execution_count": 10
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 打印系统信息",
   "id": "8517d55b85980bbc"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-03-07T12:23:17.393752Z",
     "start_time": "2025-03-07T12:23:17.390481Z"
    }
   },
   "cell_type": "code",
   "source": [
    "print(sys.version_info)\n",
    "for module in mpl, np, pd, sklearn, torch:\n",
    "    print(module.__name__, module.__version__)\n",
    "\n",
    "device = torch.device(\"cuda:0\") if torch.cuda.is_available() else torch.device(\"cpu\")\n",
    "print(device)"
   ],
   "id": "a1330eeaadd0ce47",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sys.version_info(major=3, minor=12, micro=3, releaselevel='final', serial=0)\n",
      "matplotlib 3.9.1\n",
      "numpy 2.0.0\n",
      "pandas 2.2.2\n",
      "sklearn 1.6.1\n",
      "torch 2.6.0+cu126\n",
      "cuda:0\n"
     ]
    }
   ],
   "execution_count": 11
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 加载数据集以及数据预处理",
   "id": "f8350d8c5201a17e"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-03-07T12:23:17.423746Z",
     "start_time": "2025-03-07T12:23:17.397755Z"
    }
   },
   "cell_type": "code",
   "source": [
    "\n",
    "transform = transforms.Compose([\n",
    "    transforms.ToTensor(),  # 将图片转换为tensor\n",
    "    transforms.Normalize((0.2860,), (0.3205,))  # 归一化\n",
    "])\n",
    "\n",
    "train_ds = datasets.FashionMNIST(\n",
    "    root=\"data\",\n",
    "    train=True,\n",
    "    download=True,\n",
    "    transform=transform\n",
    ")\n",
    "\n",
    "test_ds = datasets.FashionMNIST(\n",
    "    root=\"data\",\n",
    "    train=False,\n",
    "    download=True,\n",
    "    transform=transform\n",
    ")\n"
   ],
   "id": "1771d002fbeab091",
   "outputs": [],
   "execution_count": 12
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-03-07T12:23:17.454400Z",
     "start_time": "2025-03-07T12:23:17.423746Z"
    }
   },
   "cell_type": "code",
   "source": [
    "\n",
    "transform = transforms.Compose([\n",
    "    transforms.ToTensor(),  # 将图片转换为tensor\n",
    "    transforms.Normalize((0.2860,), (0.3205,))  # 归一化\n",
    "])\n",
    "\n",
    "train_ds = datasets.FashionMNIST(\n",
    "    root=\"data\",\n",
    "    train=True,\n",
    "    download=True,\n",
    "    transform=transform\n",
    ")\n",
    "\n",
    "test_ds = datasets.FashionMNIST(\n",
    "    root=\"data\",\n",
    "    train=False,\n",
    "    download=True,\n",
    "    transform=transform\n",
    ")\n",
    "\n",
    "# torchvision 数据集里没有提供训练集和验证集的划分\n",
    "# 当然也可以用 torch.utils.data.Dataset 实现人为划分\n",
    "# 从数据集到dataloader\n",
    "batch_size = 64\n",
    "train_loader = torch.utils.data.DataLoader(train_ds, batch_size, shuffle=True)\n",
    "val_loader = torch.utils.data.DataLoader(test_ds, batch_size, shuffle=False)"
   ],
   "id": "92c6c3ebb2e3661f",
   "outputs": [],
   "execution_count": 13
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 定义模型",
   "id": "278f23af3d1f8c13"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-03-07T12:23:17.464467Z",
     "start_time": "2025-03-07T12:23:17.454400Z"
    }
   },
   "cell_type": "code",
   "source": [
    "class NeuralNetwork(nn.Module):\n",
    "    def __init__(self, layers_num=2):\n",
    "        super().__init__()\n",
    "        self.transforms = transforms  # 预处理层，标准化\n",
    "        self.flatten = nn.Flatten()\n",
    "        # 多加几层\n",
    "        self.linear_relu_stack = nn.Sequential(\n",
    "            nn.Linear(28 * 28, 100),\n",
    "            # 这里先激活函数后batch norm，是因为batch norm 依赖于激活函数的输出\n",
    "            nn.BatchNorm1d(100),  # num of features=100\n",
    "            nn.SELU(),\n",
    "        )\n",
    "        # 加19层:所谓的DNN就是多个全连接层堆叠而成add_module()方法可以添加多个模块\n",
    "        for i in range(1, layers_num):\n",
    "            self.linear_relu_stack.add_module(f\"Linear_{i}\", nn.Linear(100, 100))\n",
    "            self.linear_relu_stack.add_module(f\"relu\", nn.ReLU())\n",
    "        # 输出层\n",
    "        self.linear_relu_stack.add_module(\"Output Layer\", nn.Linear(100, 10))\n",
    "\n",
    "        # 初始化权重\n",
    "        self.init_weights()\n",
    "\n",
    "    def init_weights(self):\n",
    "        \"\"\"使用 xavier 均匀分布来初始化全连接层的权重 W\"\"\"\n",
    "        # print('''初始化权重''')\n",
    "        for m in self.modules():\n",
    "            if isinstance(m, nn.Linear):  #判断m是否为全连接层\n",
    "                nn.init.xavier_uniform_(m.weight)  # xavier 均匀分布初始化权重\n",
    "                nn.init.zeros_(m.bias)  # 全零初始化偏置项\n",
    "        # print('''初始化权重完成''')\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = self.flatten(x)\n",
    "        # 展平后 x.shape [batch size, 28 * 28]\n",
    "        logits = self.linear_relu_stack(x)\n",
    "        # logits.shape [batch size, 10]\n",
    "        return logits\n",
    "\n",
    "\n",
    "model = NeuralNetwork(layers_num=10)\n",
    "total = 0\n",
    "# 计算模型参数数量\n",
    "for idx, (key, value) in enumerate(NeuralNetwork(20).named_parameters()):\n",
    "    # print(f\"Linear_{idx // 2:>02}\\tparamerters num: {np.prod(value.shape)}\") #np.prod是计算张量的元素个数\n",
    "    # print(f\"Linear_{idx // 2:>02}\\tshape: {value.shape}\")\n",
    "    total += np.prod(value.shape)\n",
    "total  #模型参数数量\n"
   ],
   "id": "11423c1b59a22cfb",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(271610)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 14
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 定义评估函数",
   "id": "ecd4a0058ad34182"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-03-07T12:23:17.468269Z",
     "start_time": "2025-03-07T12:23:17.464467Z"
    }
   },
   "cell_type": "code",
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "\n",
    "@torch.no_grad()\n",
    "def evaluating(model, dataloader, loss_func):\n",
    "    loss_list = []\n",
    "    pred_list = []\n",
    "    label_list = []\n",
    "    for datas, labels in dataloader:\n",
    "        datas = datas.to(device)\n",
    "        labels = labels.to(device)\n",
    "        # 前向计算\n",
    "        logits = model(datas)\n",
    "        loss = loss_func(logits, labels)  # 验证集损失\n",
    "        loss_list.append(loss.item())\n",
    "\n",
    "        preds = logits.argmax(axis=-1)  # 验证集预测\n",
    "        pred_list.extend(preds.cpu().numpy().tolist())\n",
    "        label_list.extend(labels.cpu().numpy().tolist())\n",
    "\n",
    "    acc = accuracy_score(label_list, pred_list)\n",
    "    return np.mean(loss_list), acc\n"
   ],
   "id": "2524cddf69753ec4",
   "outputs": [],
   "execution_count": 15
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 训练函数",
   "id": "260c25953b4b2eff"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-03-07T12:23:17.474839Z",
     "start_time": "2025-03-07T12:23:17.468269Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# 训练\n",
    "def training(\n",
    "        model,\n",
    "        train_loader,\n",
    "        val_loader,\n",
    "        epoch,\n",
    "        loss_func,\n",
    "        optimizer,\n",
    "        tensorboard_callback=None,\n",
    "        save_ckpt_callback=None,\n",
    "        early_stop_callback=None,\n",
    "        eval_step=500,\n",
    "):\n",
    "    record_dict = {\n",
    "        \"train\": [],\n",
    "        \"val\": []\n",
    "    }\n",
    "\n",
    "    global_step = 0\n",
    "    model.train()\n",
    "    with tqdm(total=epoch * len(train_loader)) as pbar:\n",
    "        for epoch_id in range(epoch):\n",
    "            # training\n",
    "            for datas, labels in train_loader:\n",
    "                datas = datas.to(device)\n",
    "                labels = labels.to(device)\n",
    "                # 梯度清空\n",
    "                optimizer.zero_grad()\n",
    "                # 模型前向计算\n",
    "                logits = model(datas)\n",
    "                # 计算损失\n",
    "                loss = loss_func(logits, labels)\n",
    "                # 梯度回传\n",
    "                loss.backward()\n",
    "                # 调整优化器，包括学习率的变动等\n",
    "                optimizer.step()\n",
    "                preds = logits.argmax(axis=-1)\n",
    "\n",
    "                acc = accuracy_score(labels.cpu().numpy(), preds.cpu().numpy())\n",
    "                loss = loss.cpu().item()\n",
    "                # record\n",
    "\n",
    "                record_dict[\"train\"].append({\n",
    "                    \"loss\": loss, \"acc\": acc, \"step\": global_step\n",
    "                })\n",
    "\n",
    "                # evaluating\n",
    "                if global_step % eval_step == 0:\n",
    "                    model.eval()\n",
    "                    val_loss, val_acc = evaluating(model, val_loader, loss_func)\n",
    "                    record_dict[\"val\"].append({\n",
    "                        \"loss\": val_loss, \"acc\": val_acc, \"step\": global_step\n",
    "                    })\n",
    "                    model.train()\n",
    "\n",
    "                    # 1. 使用 tensorboard 可视化\n",
    "                    if tensorboard_callback is not None:\n",
    "                        tensorboard_callback(\n",
    "                            global_step,\n",
    "                            loss=loss, val_loss=val_loss,\n",
    "                            acc=acc, val_acc=val_acc,\n",
    "                            lr=optimizer.param_groups[0][\"lr\"],\n",
    "                        )\n",
    "\n",
    "                    # 2. 保存模型权重 save model checkpoint\n",
    "                    if save_ckpt_callback is not None:\n",
    "                        save_ckpt_callback(global_step, model.state_dict(), metric=val_acc)\n",
    "\n",
    "                    # 3. 早停 Early Stop\n",
    "                    if early_stop_callback is not None:\n",
    "                        early_stop_callback(val_acc)\n",
    "                        if early_stop_callback.early_stop:\n",
    "                            print(f\"Early stop at epoch {epoch_id} / global_step {global_step}\")\n",
    "                            return record_dict\n",
    "\n",
    "                # udate step\n",
    "                global_step += 1\n",
    "                pbar.update(1)\n",
    "                pbar.set_postfix({\"epoch\": epoch_id})\n",
    "\n",
    "    return record_dict\n"
   ],
   "id": "544b6330cdef4aec",
   "outputs": [],
   "execution_count": 16
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 画图函数",
   "id": "b817d86b570d15c"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-03-07T12:23:17.482856Z",
     "start_time": "2025-03-07T12:23:17.474839Z"
    }
   },
   "cell_type": "code",
   "source": [
    "#画线要注意的是损失是不一定在零到1之间的\n",
    "def plot_learning_curves(record_dict, sample_step=500):\n",
    "    # build DataFrame\n",
    "    train_df = pd.DataFrame(record_dict[\"train\"]).set_index(\"step\").iloc[::sample_step]\n",
    "    val_df = pd.DataFrame(record_dict[\"val\"]).set_index(\"step\")\n",
    "    # print(train_df.head())\n",
    "    # print(val_df.head())\n",
    "    # plot\n",
    "    fig_num = len(train_df.columns)  #因为有loss和acc两个指标，所以画个子图\n",
    "    fig, axs = plt.subplots(1, fig_num, figsize=(5 * fig_num, 5))  #fig_num个子图，figsize是子图大小\n",
    "    for idx, item in enumerate(train_df.columns):\n",
    "        #index是步数，item是指标名字\n",
    "        axs[idx].plot(train_df.index, train_df[item], label=f\"train_{item}\")\n",
    "        axs[idx].plot(val_df.index, val_df[item], label=f\"val_{item}\")\n",
    "        axs[idx].grid()\n",
    "        axs[idx].legend()\n",
    "        x_data = range(0, train_df.index[-1], 5000)  #每隔5000步标出一个点\n",
    "        axs[idx].set_xticks(x_data)\n",
    "        axs[idx].set_xticklabels(map(lambda x: f\"{int(x / 1000)}k\", x_data))  #map生成labal\n",
    "        axs[idx].set_xlabel(\"step\")\n",
    "\n",
    "    plt.show()"
   ],
   "id": "3e41efcf7604f0e5",
   "outputs": [],
   "execution_count": 17
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# 网格搜索，for循环实现",
   "id": "fd6efd1881d23eb9"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-03-07T12:29:23.488206Z",
     "start_time": "2025-03-07T12:23:17.482856Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# for lr in [1e-2]:\n",
    "for lr in [1e-2, 3e-2, 3e-1, 1e-3]:\n",
    "    epoch = 10\n",
    "\n",
    "    model = NeuralNetwork()\n",
    "    # 1. 定义损失函数 采用交叉熵损失\n",
    "    loss_func = nn.CrossEntropyLoss()\n",
    "    # 2. 定义优化器 采用SGD\n",
    "    # Optimizers specified in the torch.optim package\n",
    "    optimizer = torch.optim.SGD(model.parameters(), lr=lr, momentum=0.9)\n",
    "    # 把模型丢到GPU上\n",
    "    model = model.to(device)\n",
    "    record = training(\n",
    "        model,\n",
    "        train_loader,\n",
    "        val_loader,\n",
    "        epoch,\n",
    "        loss_func,\n",
    "        optimizer,\n",
    "        eval_step=len(train_loader)\n",
    "    )\n",
    "    print(\"lr: {}\".format(lr))\n",
    "    plot_learning_curves(record)\n",
    "    model.eval()\n",
    "    loss, acc = evaluating(model, val_loader, loss_func)\n",
    "    print(f\"loss:{loss:.4f}\\naccuracy:{acc:.4f}\")"
   ],
   "id": "3849b365f6c517c1",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  0%|          | 0/9380 [00:00<?, ?it/s]"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "c4659070b8884360a21156ee18bc5c17"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lr: 0.01\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss:0.3338\n",
      "accuracy:0.8809\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "  0%|          | 0/9380 [00:00<?, ?it/s]"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "fd5f25359b9848f9b624be2002ac851c"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lr: 0.03\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss:0.3393\n",
      "accuracy:0.8848\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "  0%|          | 0/9380 [00:00<?, ?it/s]"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "2cec273ed47d4f45b5fee572ca213d1b"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lr: 0.3\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss:0.5953\n",
      "accuracy:0.8336\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "  0%|          | 0/9380 [00:00<?, ?it/s]"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "8119cf837dd84042b91c368c914db0c3"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lr: 0.001\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss:0.3662\n",
      "accuracy:0.8684\n"
     ]
    }
   ],
   "execution_count": 18
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
